You can work with a `Jupyter`

notebook using `Stata`

just as you would using Python. Text and math can be written in Markdown as we have done in the other notebooks. So, use your usual `Stata`

code in `code cells`

, produce figures etc., as if you were in the `Stata`

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You can work with `Stata`

in a `Python`

notebook by using the package `ipystata`

. Just like `r2py`

, which allows us to use `R`

in `Python`

, we can now use both (or if you want all three!) programming languages in one notebook.

Let's start by importing all the packages we want to use.

more ...We have studied the theory of dynamic programming in discrete time under certainty. Let's review what we know so far, so that we can start thinking about how to take to the computer.

We want to find a sequence $\{x_t\}_{t=0}^\infty$ and a function $V^*:X\to\mathbb{R}$ such that

$$V^{\ast}\left(x_{0}\right)=\sup\limits _{\left\{ x_{t}\right\} _{t=0}^{\infty}}\sum\limits _{t=0}^{\infty}\beta^{t}U(x_{t},x_{t+1})$$ more ...This notebook will introduce you to working with data in `Python`

. You will use packages like `Numpy`

to manipulate, work and do computations with arrays, matrices, and such, and anipulate data (see my Introduction to Python). But given the needs of economists (and other scientists) it will be advantageous for us to use pandas
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There are many sources of GIS data. Here are some useful links:

- WorldMap
- FAO's GeoNetwork
- IPUMS USA Boundary files for Censuses
- IPUMS International Boundary files for Censuses
- GADM database of Global Administrative Areas
- Global Administrative Unit Layers
- Natural Earth: All kinds of geographical, cultural and socioeconomic variables
- Global Map
- Digital Chart of the World more ...

GIS refers to methods of storing, displaying and analyzing geogaphical information. These methods have become essential in economic analysis (as you have noticed from the reading list for our Ph.D. course on economic growth). For this reason, it is good that you acquaint yourself with these methods. They will prove very useful when doing research, especially to show the spatial distribution of your variables of interest, contructing new measures, or doing spatial analysis.

more ...**Python** is a powerful and easy to use programming language. It has a large community of developers and given its open source nature, you can find many solutions, scripts, and help all over the web. It is easy to learn and code, and faster than other high-level programming languages...and did I mention it is *free*
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